@ godfrey
thanks。刚试了一下，source -> Deduplicate ->
GlobalGroupAggregate,在souce端确实是复用了。但是Deduplicate 端是没有复用呢？理论上source +
Deduplicate 都是view里的逻辑，都应该复用才对。就是感觉复用的还不够多呢。
在 2020-08-04 17:26:02，"godfrey he" <godfre...@gmail.com> 写道：
>blink planner支持将多sink的query优化成尽量复用重复计算部分。
>1.11里用StatementSet来提交job，1.11之前用sqlUpdate/insertInto + execute提交任务
>
>kandy.wang <kandy1...@163.com> 于2020年8月4日周二 下午5:20写道：
>
>> FLINK SQL view相关问题：
>> create view order_source
>>
>> as
>>
>> select order_id, order_goods_id, user_id,...
>>
>> from (
>>
>> ...... proctime,row_number() over(partition by order_id,
>> order_goods_id order by proctime desc) as rownum
>>
>> from hive.temp_dw.dm_trd_order_goods/*+
>> OPTIONS('properties.group.id'='flink_etl_kafka_hbase',
>> 'scan.startup.mode'='latest-offset') */
>>
>> ) where rownum = 1 and price > 0;
>>
>>
>>
>>
>> insert into hive.temp_dw.day_order_index select rowkey, ROW(cast(saleN as
>> BIGINT),)
>>
>> from
>>
>> (
>>
>> select order_date as rowkey,
>>
>> sum(amount) as saleN,
>>
>> from order_source
>>
>> group by order_date
>>
>> );
>>
>>
>>
>>
>> insert into hive.temp_dw.day_order_index select rowkey, ROW(cast(saleN as
>> BIGINT))
>>
>> from
>>
>> (
>>
>> select order_hour as rowkey, sum(amount) as saleN,
>>
>>
>>
>> from order_source
>>
>> group by order_hour
>>
>> );
>> 问题：同一个view，相同的消费group,不同的sink,产生 2个job。 这样的话，相当于2个job公用一个consumer group。
>> 最后生成的job是 : a. order_source -> sink 1 b. order_source -> sink
>> 2
>>
>>
>> 本意是想通过view order_source
>> （view里需要对订单数据去重）复用同一份source全量数据,对应底层可以复用同一份state数据 ，如何做到 ？
>>
>>
